Restructuring computer programs

ABSTRACT

A method of restructuring a source computer program to a target computer program. A defined source computer program has source code. A set of tasks is defined for the source computer program to be performed by the source computer program. For each task, a corresponding set of input data sets is defined. For each input data set, a corresponding set of programs is determined such that each program in the set of programs includes declarations and executable statements, from the source code of the source computer program, required to execute the task in each input data set. Each set of programs is processed to generate a component that executes the respective task, resulting in generation of a set of components. A target computer program is generated from the set of components.

This application is a divisional of Ser. No. 10/229,795, filed Aug. 27, 2002.

FIELD OF THE INVENTION

The present invention relates to the restructuring of computer programs, to assist in improving the ability to understand, port, and maintain the code of such computer programs.

BACKGROUND

Many early computer programs were written in a relatively haphazard manner. As a result, many of these programs can be very difficult to understand due to the complexity and lack of structure of the underlying code, which is often referred to as “spaghetti code” due to this unstructured complexity.

Such unstructured computer programs rarely have any reliable explanatory documentation. Further, the original developers of these computer programs are typically no longer available for consultation. Understandably, the maintenance, modification, and porting of such computer programs is, as a result, particularly difficult.

Over the years, a huge investment has been made in such computer programs that are often used in critical operations or applications, often referred to in this context as “legacy applications”. These legacy applications have earned the trust and confidence of their users for the simple reason that they operate as expected.

The owners of legacy computer applications increasingly wish to port their applications to new computing environments, especially if existing computing environments are no longer supported at the hardware or operating system level. The transition of such applications to new computing environments is usually preferred, compared to other possible options, such as re-writing the relevant application. However, there is often little if any adequate supporting documentation that might assist in making this transition. Consequently, the task of porting the legacy application to a new platform can be an unpredictable and expensive undertaking when manually performed.

Accordingly, a need clearly exists for an improved manner of restructuring computer programs that at least attempts to address one or more existing limitations of the prior art.

SUMMARY

An existing computer program is restructured to a new computer program such that the new computer program performs all (or a desired subset) of the tasks performed by the existing computer program.

Experienced users of the existing program assist with the identification and selection of tasks to be performed by the restructured program, and, for each task, the generation of a reliable and comprehensive set of test cases used to verify the correct functioning of the restructured program. Such experienced users, due to their long familiarity and use of the existing program, can provide detailed information about: (i) the tasks for which the original computer program is used, (ii) the inputs (including their valid ranges) related to each of the tasks required to be performed by the program, (iii) the outputs generated by the program, and (iv) known but unfixed bugs. The test cases are also used to restructure the existing program.

Particular advantages that accrue from restructuring computer programs include easier maintenance of the restructured program compared to the original computer program. The described techniques are particularly useful for maintaining legacy codes or applications for which reliable documentation is either not available or inadequate. The restructured program can be more readily used than the original program as a baseline against which further enhancements can be added to the program. Such further enhancements may include, for example, introduction of fresh code for new tasks to be performed by the restructured program.

DESCRIPTION OF DRAWINGS

FIG. 1 is a flowchart of the steps involved in a technique for restructuring a computer program.

FIG. 2 is a flowchart of the steps involved in preformatting a computer program to be restructured in accordance with FIG. 1.

FIGS. 3 to 19 provide computer code of a first described example relating to restructuring of computer code, while FIGS. 20 to 24 provide code of a second described example relating to restructuring of computer code.

FIGS. 3 to 5 provide computer code for a full program for the first example.

FIGS. 6 to 8 provide computer code corresponding with that of FIGS. 3 to 5, when recast in canonical form.

FIGS. 9 and 10 provide computer code extracted from the canonical form of code provided in FIGS. 6 to 8, for performing a task T₁.

FIGS. 11 and 12 reproduce the computer code from FIGS. 9 and 10 with the functions, including main( ), renamed.

FIGS. 13 and 14 provide computer code extracted from the canonical form of code provided in FIGS. 6 to 8, for performing a task T₂. The functions in the extracted code are renamed.

FIG. 15 provides computer code extracted from the canonical form of code provided in FIGS. 6 to 8, for performing a task T₃. The functions in the extracted code are renamed.

FIGS. 16 to 19 provide computer code corresponding with that of FIGS. 3 to 5, in which the whole computer code is restructured.

FIGS. 20 and 21 provide computer code of a second described example, in which there are three separate versions of the func( ) function.

FIGS. 22 and 23 provide computer code corresponding with that of FIGS. 20 and 21, in which the different versions of func( ) function are merged and sorted.

FIG. 24 provides computer code corresponding with that of FIGS. 20 and 21, in which there is a revised listing of the func( ) function.

FIG. 25 is a schematic drawing of a computing system for performing the techniques described with reference to FIGS. 1 to 24.

DETAILED DESCRIPTION

Techniques for restructuring computer programs are described herein. A computer system, and computer software for use in performing these techniques are also described herein.

Terminology

Various terms are used herein, explanatory definitions for which are given below.

Program: A computer program comprises a main function definition. The computer program can further comprise one or more other function definitions. The main function definition, and any other function definitions, can appear in any order. The distinction between the main function, and any other functions, is that when a computer program is first invoked for execution, the program executes with the first executable statement in the main function definition. That is, the computing environment calls the main function to execute the program. The main function returns a value to the environment in which the program executes.

Function: A function is also known as a subroutine, subprogram, procedure in the literature. A function is characterized by a name, a list of parameters, a sequence of actions, and a datatype of the return value of the function.

Function definition: A function definition encodes the characteristics of a function in a suitable format, such as:

Return-datatype function-name (parameter declaration, if any) { declarations and statements }

The term parameter is generally used for a variable named in the parenthesized list in a function definition, while the term argument is generally used for the value of the parameter used in a call of the function. The declarations and statements within the curly brackets are also known as the function body. These declarations and statements encode a sequence of actions performed by the function, as well as any supporting declarations. float f(float b, float c) // This line is the { // function's declaration. float g, h; g = b + 2*c; // Contents within curly h = c; // brackets form the return g*h + 1; // function's body. }

The example function's declaration can be interpreted as describing a function whose name is f and whose parameters are b of data type float and c of data type float. The function float f (float b, float c) returns a value whose data type is float. The statements constituting the function's body carry out actions necessary to compute the return value.

Problem Definition

Consider a program P (that is, the legacy application, for example) that comprises a main function definition F₀. The program P optionally comprises one or more other function definitions F₁, F₂, . . . F_(r). Thus the program represents the set P={F₀, F₁, F₂, . . . F_(r)}.

Associated with P is the set of tasks T={T₁, T₂, . . . T_(n)}. Each task, if appropriate input data is provided, is performed by program P. T is also the set of tasks the restructured version of P is expected to perform in a manner P would have if given identical inputs. P may have additional task performing abilities but they are of no concern in the restructured version.

The restructuring of P results in another program P_(R) such that P_(R)={M_(R), C₁, C₂, . . . C_(n)}, where a C_(i), referred to herein as a component, contains all the required declarations and executable statements extracted from P required to execute the task T_(i). M_(R) is a newly created main function for P_(R) whose principal task is to ascertain which task the user wishes to invoke and ensure the execution of the corresponding component C_(i) to execute the task.

Typically, component C_(i) can be viewed as the set of functions C_(i)={F_(0i), F_(1i), F_(2i), . . . F_(ri)}, where F_(0i) contains all the declarations and executable statements extracted from F₀ in the context of executing the task T_(i) but packaged as a function, and, likewise, each function F_(ki), k>0, contains all the declarations and executable statements extracted from F_(k). Note that the structure of P_(R) is such that if a task T_(j) is modified, or eliminated, only C_(j) is modified, or eliminated along with its corresponding code in M_(R), while the rest of P_(R) remains unchanged.

Although the code size of P_(R) is usually expected to be larger than that of P, P_(R) is generally expected to be better understood than P, especially if P is coded in “spaghetti” fashion. Accordingly, P_(R) can be expected to be better optimizable than P on a task-by-task basis.

Overview

With reference to the above “Problem definition” subsection, an overview of the described restructuring process is described with reference to FIGS. 1 and 2.

FIG. 1 is a flowchart of the steps involved in the restructuring process. In step 110, a source computer program P is defined. In step 120, a set of tasks T from the tasks performed by program P is selected. In step 130, data sets U_(i) are determined for respective tasks T_(i) from the set of tasks T. Once steps 110 to 130 are performed, the source program P is restructured into corresponding target computer program P_(R) in step 140.

FIG. 2 is a flowchart of the steps involved in preformatting the source program P prior to restructuring the program as target program P_(R). In step 210, the source program P is reformatted according to predetermined formatting rules. Then, statements in reformatted source program P are converted to a canonical form in step 220. This canonical form may be predetermined, or selected from one or a number of possible predetermined canonical forms. A particular canonical form may be selected as most appropriate given the existing form of the source program P.

In step 230, a line number is provided for each line of the reformatted and converted source program P. At this stage, the source program P is executed in step 240 using a restructuring interpreter to initiate the restructuring process.

The above overview of the process of restructuring a computer program is described in further detail below.

Restructuring Process

The fundamental assumption for developing the restructuring method is that a properly documented list of tasks can be created, if necessary, by experienced users of program P and that the resulting document may be considered as a requirements document for the program P_(R).

Once the tasks have been identified, the restructuring process can be performed in three parts.

1. Creation of input data sets for each task in T.

2. Creation of components C₁, C₂, . . . C_(n) and M_(R).

3. Manual optimization of P_(R).

Creation of Input Data Sets for Each Task in T

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A known set of tasks, including the set T, and a source for obtaining (or an ability to create) valid input data sets for desired coverage of the tasks is assumed for program P.

Hence specifying the tasks set T, and for each task in T, creating one or more input data sets to provide complete coverage of the task is expected to be achievable. For example, one may collate input data from past input data files to P for the chosen task.

A group of input data sets U_(i)={u_(i1), u_(i2), . . . u_(ip)} is available whose individual members may carry out either the complete task T_(i) or a subtask of T_(i). Note that, in general, p is not constant but is a function of i; that is, p=p(i). Collectively each group of input data sets provides full coverage for executing task T_(i). Data boundaries for task T_(i) are assumed to be known, and these data boundaries are assumed to be accounted for in U_(i).

Furthermore, assume that no member u_(ij) of U_(i) creates error conditions when used as input to the program P.

Creation of Components C₁, C₂, . . . C_(n) and M_(R)

This part of the described program restructuring technique has 11 steps, as described below.

Step 1—Reformatting Original Code

First, program P is reformatted (if not already in the desired format) according to a predefined set of rules.

For example, these predetermined formatting rules may involve:

-   (i) arranging function definitions F₀, F₁, F₂, . . . F_(r) in an     ASCII ascending order of the function's name; -   (ii) replacing multiple blanks in statements with a single blank     wherever permissible; -   (iii) indenting blocks of statements according to their nesting     order; -   (iv) removing redundant brackets, etc

These rules facilitate character string comparisons between any two parts of P. Many modern programming languages (such as C and C++) provide functions for character string operations. For example, these character string operations can include functions for finding a string, comparing two strings, and deleting a string. Such functions can be used to implement the application of predetermined formatting rules to the original code.

Conditional constructs may require careful reformatting in some programming languages. Some programming languages allow for premature termination of a conditional construct, if the evaluation of a subset of the total conditions unambiguously determines the final Boolean result of the conditional construct. Consider the following example:

if (j<0 && k<1∥k>10) then { . . . }

A final Boolean result of TRUE is determined, irrespective of the result of evaluating k>10 if j<0 && k<1 is TRUE. Further, in j<0 && k<1 one may conclude that the result is FALSE if j>=0 without determining if k<1. For such constructs, one may, for example, format the statement as follows:

if (

j<0

&& k<1

∥k>10

)

then { . . . }

The restructuring interpreter is appropriately programmed to handle statements formatted in this way. The above described formatting of the conditional statement is used to achieve various benefits described herein. These benefits are clear from the following description in relation to:

(a) the second and third steps noted below, (b) step 7—merging of variants of a function in C_(i) or step 8—merging of variants of a function across C_(i).

The required formatting for a given programming language can be determined as appropriate.

Step 2—Converting to Canonical Forms

Second, statements or blocks of statements are converted into a canonical form wherever possible. That is, if more than one way of expressing statement(s) is available, then only one from the many ways of expression is chosen as the canonical form and all instances of other forms are converted to the canonical form. For example, if a++ and a=a+1, both appear then choose one of them, say, a++ as the canonical form and convert instances of a=a+1 into a++.

Another example is the switch-case statement, a representation of which is given directly below. switch(j) { case 1: ... ... ...; break; case 2: ... ... ...; break; ... ... ... ... ... ... ... ... ... ... case 6: ... ... ...; break; default: break; }

If an alternative if-else construct is chosen as the canonical form then the above example is restructured as follows: if (j == 1) then {. . .}; else if (j == 2) then {. . .}; ... ... ... ... ... ... ... ... else if (j == 6) the {. . .}; else {. . .};

A sequence of else-ifs can be arranged in ASCII order of the conditions contained in the if-else construct. Such arrangement is possible if semantic correctness can be maintained in the reordering so that equivalence of condition groups can be caught if they appear in different permutations in different parts of P.

In yet another example, consider a while statement such as: while (i > 0) { a++; i−−; }

This statement can be converted to an if statement: s10: if (i > 0) then { a++; i−−; goto s10; }

The use of canonical forms makes equivalent code segments easier to detect especially using automated tools.

Step 3—Line Numbering

Third, each line in the program P is provided with a unique line number, preferably in ascending order. Line numbering facilitates the location of particular code fragments.

The following statement has only one associated line number (in this case, 11), as the statement only appears on one line:

11 if (j<0 && k<1∥k>10) then a=a*b+1;

equivalent code is given below: 32  if (j < 0 33  && k < 1 34  || k > 10 ) 35  then a = a*b + 1;

This equivalent code has four associated line numbers (in this case, 32-35), as the code appears over four lines.

Step 4—Program Execution—Use of Flags

The program P is executed by a tool that can be considered to be a restructuring interpreter. After performing steps 1 to 3 described above, the program P is executed for each user input data set in U_(i), say u_(ij), related to the task T_(i). The essential difference between a conventional interpreter (or a debugger) and a restructuring interpreter is that the restructuring interpreter flags every statement or part of a statement that the restructuring interpreter executes.

Assignment statements, if executed, are executed completely. By contrast, if statements are sometimes partially executed, as noted above.

When the restructuring interpreter is executing the program P, three kinds of flags are used.

-   (i) The first flag is placed on a statement (or part of a statement)     just before the restructuring interpreter begins execution. -   (ii) The second flag replaces the first flag as soon as the     execution of the statement (or part of a statement) is completed. -   (iii) A third flag is placed on a statement (or part of a statement)     if the statement is being executed more than once while executing     with input data u_(ij).

A statement (or part of a statement) being reexecuted has two flags—first and third flags just prior to beginning of execution, and second and third flag on completion of execution.

If a program terminates abnormally while executing a statement (or part of a statement), the “maverick” statement can be detected. Detection is possible, as this maverick statement is the only statement that has a first flag that is not tagged to a function call that has not been completed.

All other statements with only a first flag will necessarily be a call to a function. Until the call is completed, the first flag remains. If there are several statements with only a first flag, these statements belong to a sequence of nested function calls, and the maverick statement belongs to the body of the last called function in this sequence of nested call functions.

The main use of the third flag is to draw attention to frequently executed statements that might benefit from manual optimization.

Reformatting of P is essentially a means of making the restructuring interpreter's tasks of flagging easier.

Step 5—Extraction of Code from P for Creating Components C_(i)

After completing execution of program P with input data u_(ij) (a) all unflagged executable statements (or substatements, where appropriate) from program P are deleted, and (b) all declarations redundant to the remaining executable statements in program P are deleted. A version of component C_(i), referred to as c_(ij), with respect to u_(ij), is thus captured. At this stage each c_(ij) comprises two parts:

-   (i) declarations and statements that were extracted from F₀ of P and     which are to be packaged as a normal function rather than as a main     function into f_(0ij), and -   (ii) f_(1ij), f_(2ij), . . . f_(rij) comprising declarations and     statements extracted from F₁, F₂, . . . F_(r), respectively.

In general, c_(ij)={f_(0ij), f_(1ij), f_(2ij), . . . f_(rij). However, if a function, for example, F_(k) is not called while executing P with input data u_(ij), then f_(kij) is absent from cu.

In essence, c_(ij) is a complete program with f_(0ij) as its defacto main function. The code c_(ij) is a complete program for all such data for which u_(ij) is a representative example. Thus, one may view c_(ij) as a program that runs a subtask of T_(i). Note that c_(ij) necessarily exists as u_(ij) is a data set chosen such that P is executed.

C_(i) can be constructed from the assembled c_(ij), j=1, 2, . . . p(i). Steps 6 to 8 show how this can be done efficiently by retaining, in the assembled c_(ij), only one copy of a function definition appearing more than once and by merging different variations of a function definition into a single function definition.

Step 6—Retaining One Copy from Multiple Copies of a Function Definition

This step is described by the following pseudo-code fragment. // Pseudo-code fragment do k = 1, 2, ... p(i) − 1 { if c_(ik) is not found, continue do l = k+1, k+2, ... p(i) { if c_(il) is not found, continue String compare c_(ik) and c_(il). if c_(ik) = c_(il) then delete c_(il) and continue. do m = 0, 1, 2, ... r { if f_(mil) or f_(mik) is not found, continue String compare f_(mik) and f_(mil). if f_(mik) = f_(mil) then delete f_(mil). } } −400}

Note that string comparisons can be made to determine if c_(ik)=c_(il) or f_(mik)=f_(mil) if each entity is formatted to a canonical form.

No two function definitions are now identical in C_(i), because as may be seen from the above pseudocode, all but one copy of a function definition is retained, and other copies, if any, are deleted. However, two or more function definitions with the same function declaration but different body contents may exist. A means of merging a group of function definitions with the same function declaration into a single function definition is described directly below.

Step 7—Merging Variants of a Function in C_(i)

Let two functions f_(mik) and f_(mil) from C_(i) be two functions that share the same function declaration (that is, of F_(m)) but whose body contents are different. Since the lines in P are already numbered, the merging of the bodies of the functions f_(mik) and f_(mil) is fairly easy. To proceed, choose one of the functions, for example, f_(mik) as the anchor and append to its body the body of f_(mil). If there are more than two functions with the same function declaration in C_(i) then the bodies of each of the remaining functions are also appended one by one to the body of f_(mik). After the appending operation, sort the augmented body of f_(mik) by line number in ascending order (assuming that the line numbering in P is in ascending order). After the sorting operation, if a line number appears more than once, then for each group of lines carrying the same line number, do the following:

-   (i) if all such lines are declarations (recall that while creating     c_(ij), all declarations redundant to c_(ij) were also deleted),     consolidate their contents into a single declaration by eliminating     any duplication of information, if any; else -   (ii) if all such lines have identical text, then delete all such     lines except one; else -   (iii) if all such lines are conditional statements, delete them all     and in their place put a copy of the corresponding conditional     statement from P. In the copy, delete all conditions which have     variables that have become undeclared due to step (i).

In addition, if a group of lines in f_(mik) are identified as belonging even partially to a corresponding conditional construct in P, then:

-   (iv) delete the said group of lines from f_(mik) and in its place     copy the corresponding conditional construct from P. In the copy,     delete all conditions that have variables that have become     undeclared due to step (i).

After the merging operation is completed, retain only f_(mik) and delete all other function definitions involved in the merger.

In each C_(i), now rename all functions, for example, by tagging all function names with the task's ID, and make corresponding changes to all calls to those functions. For example, one may rename f_(mik) as funcm_i, where funcm is assumed to be the original name of f_(mik). All calls to funcm in C_(i) are now made to funcm_i.

This renaming process clearly separates different C_(i)s from each other, as there are no function name clashes among the various tasks. Separating tasks in this manner allows task-related modifications to be done without interfering with code for other tasks. The renaming process also applies to the “main” function f_(0ik) of C_(i). All the other main functions f_(0il) of C_(i) merge to the “main” function f_(0ik) of C_(i) if f_(0ik), which is always there for all permissible values of k (that is, k=1, 2, . . . r), is chosen as the anchor.

Step 8—Merging Variants of a Function Across C_(i)

The size of P_(R) may be quite large even after the merging of variants of a function in C_(i). The relatively large size of P_(R) is attributable to each C_(i) carrying a variant f_(k) _(—) _(i) of F_(k), k=1, 2, . . . r. Furthermore, for ease of understanding, the number of new function names is desirably reduced, if possible. Thus, as many of the f_(k) _(—) _(i), i=1, 2, . . . n as possible are merged, and revert to original function names wherever possible, within P_(R). Variants of F₀ are excluded to maintain task identity. To accomplish a possible reduction in function names, the following steps are performed for k>0:

-   1. If there is at least one f_(k) _(—) _(i) whose contents are     identical to those of F_(k), then delete all f_(k) _(—) _(i), i=1,     2, . . . n that exist. Copy F_(k) into P_(R) and change all calls to     f_(k) _(—) _(i) in their respective C_(i) to calls to F_(k). -   2. If two functions f_(k) _(—) _(r) and f_(k) _(—) _(s) have     identical contents but not identical to those of F_(k), delete one     of them, say, f_(k) _(—) _(s) from P_(R) and all calls to f_(k) _(—)     _(s) are then changed to calls to f_(k) _(—) _(r). Alternatively, if     only one variation of F_(k) exists, say, f_(k) _(—) _(r) whose     contents are not identical to those of F_(k), then retain f_(k) _(—)     _(r). -   3. For all left over f_(k) _(—) _(i) do the following:     -   Take all variations of F_(k), that is, functions f_(k) _(—)         _(i), i=1, 2, . . . , n which exist, and append their bodies         into a single function and refer to this single function as         f_(k) _(—) _(R). Following the append operation, sort the body         of f_(k) _(—) _(R) by line number in ascending order (this         sorting process assumes that the line numbering in P is in         ascending order). After the ordering is completed, if a line         number appears more than once, then for each group of lines         carrying the same line number, do the following:         -   (i) if all such lines are declarations, consolidate their             contents into a single declaration by eliminating any             duplication of information, if any; else         -   (ii) if all such lines have identical text, then delete all             such lines except one; else         -   (iii) if all such lines are conditional statements, delete             them all and in their place put a copy of the corresponding             conditional statement from P. In the copy, delete all             conditions that have variables that have become undeclared             following step (i).     -   In addition, if a group of lines in f_(k) _(—) _(R) are         identified as belonging even partially to a corresponding         conditional construct in P, then         -   (iv) delete the said group of lines from f_(k) _(—) _(R)             and, in its place, copy the corresponding conditional             construct from P. In the copy, delete all conditions that             have variables that have become undeclared due to step (i).     -   Delete all f_(k) _(—) _(i), i=1, 2, . . . , n. Copy f_(k) _(—)         _(R) into P_(R) and change all calls to any of the f_(k) _(—)         _(i) in P_(R) to calls to f_(k) _(—) _(R). Note that the         functions f_(k) _(—) _(R) will now be shared by all the C_(i) in         P_(R).         Step 9—Handling if-then-Else Conditions

Conditional statements are assumed to appear only in if-then-else canonical form. When such statements are executed, a syntactical convention is adopted in accordance with the example given below.

A general if-then-else condition appears as follows:

if ( . . . ) then { . . . } else { . . . }

When executing a data set, if the then clause is executed then the extracted code appears as:

if ( . . . ) then { . . . } else { }

This may be simplified to:

if ( . . . ) then { . . . }

This code can be further simplified in some cases to { . . . }. However, this simplification has not been done in this case since some programming languages permit assignment statements inside an if construct.

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Furthermore, retaining if ( . . . ) helps in the understanding of the restructured code since one is able to see the conditions that were actually invoked prior to the execution of: { . . . }.

Conversely, if the else clause is executed, the extracted code appears as:

if ( . . . ) then { } else { . . . }

The restructuring interpreter flags those conditions inside ( . . . ) that were tested, and those statements in { . . . } that were actually executed.

A particularly interesting situation occurs in the switch-case statement when only the default condition is executed. In this case, the entire switch-case statement can be replaced by the statements encapsulated with the default condition. For example, in: switch(j) { case 1: ... ... ...; break; case 2: ... ... ...; break; ... ... ... ... ... ... ... ... ... ... case 6: ... ... ...; break; default: <default-statements>; } if only the default case is executed, then the above can be simply replaced by: <default-statements>;

The if-then-else version of the above switch-case example is: if (j == 1) then {. . .}; else if (j == 2) then {. . .}; ... ... ... ... ... ... ... ... else if (j == 6) then {. . .}; else {<default-statements>};

Execution of the default case results in: if (j == 1) then { }; else if (j == 2) then { }; ... ... ... ... ... ... ... ... else if (j == 6) then { }; else {<default-statements>};

From this code, the code can be clearly further reduced to:

<default-statements>;

In any event, <default-statements> may of course be empty. As a precaution, one may choose to retain all blank then { } and else { } conditions instead of eliminating these conditions when the opportunity exists. Such precaution may be useful, for example, if there are doubts that the coverage provided by the set of tasks T is not complete, or that P has some unresolved bugs. In such cases the blank { } may be populated with a suitable error message that is activated if an attempt is made by the program to branch to a blank condition.

Step 10—Introduction of Error Handlers for Input Data

Whenever necessary, additional code is manually introduced to check all input values provided through input statements for validity and, on error, transmit error messages or call error handlers (that may also have to be manually written). The restructuring interpreter leaves a highlighted message as a reminder to the programmer. This reminder, placed immediately after an input statement, reminds the programmer that input checking and error handling code is desirable in place of the highlighted message.

Step 11—Construction of the Main Function M_(R)

The main function M_(R) for P_(R) can be created manually (although automating these tasks is also possible). Manually creating M_(R) for P_(R) is relatively simple. First, create the declarations (of variables lists, etc.). Second, create one or more conditional statements such that when input data for task T_(i) is encountered, C_(i) is executed.

The following code fragment illustrates how this process can be performed and used as a template for creating M_(R). There are 3 tasks and each task is given a unique ID, for example, 1, 2, 3. Task with ID=1 calls function f01( ), task with ID=2 calls function f02( ), and task with ID=3 calls function f03( ). Any other task ID results in an error condition. main( ) { int task_id; get_input (task_id); if (task_id == 1) then f01 ( ); else if (task_id == 2) then f02 ( ); else if (task-id == 3) then f03 ( ); else Out_err_msg ( ); end; } Manual Optimization of P_(R)

State-of-the-art optimizing compilers cannot match the optimizing abilities of expert programmers. As (i) a component C_(i) is usually smaller than the original program P and (ii) the component C_(i) will be more focussed towards a task rather than a group of tasks, the component C_(i) is comparatively easier to understand, debug, optimize, and enhance compared to the original program P. Thus individual tasks may be made to run faster in P_(R) than in P.

In manual optimization, one can frequently take advantage of the statistical fact that for large codes with many function definitions, substantial amounts of execution time is usually spent in less than 10% of the total number of functions in a program. Thus, even in a large program, the amount of code required to be optimized from a practical standpoint is usually manageable.

The functions requiring optimization can be detected by using a profiling tool with which many modern compilers are equipped with or by appropriately “instrumenting” the program P_(R) for profiling. For some legacy codes, some form of software instrumentation may be necessary. Software instrumentation can be introduced using additional code in each function (including the main function) that detects the time the function was entered, and the time when the function was exited. A running sum of the time spent in each of the functions (that is, the difference between exit and entry times) is maintained for every respective function call, to establish a pattern of function use.

As an optional feature, for a given u_(ij), one may highlight in P the declarations and statements that constitute c_(ij). Highlighting declarations and statements helps obtain an intuitive feel for how code segments in P relate to various functionalities that are distributed and mapped in P. The restructuring interpreter collates all necessary code segments in one place for subsequent manual modification.

Designing Input Data Sets

If an input data set is designed to explore a simple task, one would usually expect only a small part of the code P to execute. Thus the resulting size of the corresponding implemented code usually enables one to better understand this restructured code, optimize the code with reasonable effort, and perhaps modify the code to make the code reusable.

Some time is preferably spent exploring the program P through a series of input data sets that are devised to test very simple tasks. Then a combination of simple tasks are devised, and so on until one begins to intuitively feel how the program P operates, note redundancies in the program's coding etc. In some cases, particular coding redundancies may have been deliberately introduced in the original code to speed up execution in some specific computing environment.

By using variations of an input data set, one can compare the differences between the original program's respective executed code segments, and learn how one can favorably consolidate these code segments. By suitably changing the input parameter values over their permissible ranges in a series of runs, and comparing the resulting series of executed code segments with each other, one can extract fully restructured code for the task being studied. This process is necessary if the task produces executed code segments that contain conditional statements.

In fact, the above strategy can be usefully applied to even modern codes that require restructuring or that include errors. Input data sets devised to test suspected functionalities produce an actual list of statements that are executed. This list can be examined for correctness.

Debugging executed code segments is relatively simple compared to debugging all of P, because the smaller executed code segments can be converted into an executable program, with little programming effort.

Improving Code Delivery to Customer

Most software projects fall far behind schedule. In such situations, clients are sometimes agreeable to receiving a partial product provided that whatever functionalities are provided are robust enough to carry out a subset of the tasks required of the final product P.

The described code restructuring method can be used to make such partial deliveries of P. Such partial deliveries can be made by selecting a subset of the tasks after consulting the customer, and creating a P_(R) for those tasks from P. Subsequently, code for each additional task can be added to P_(R), one task at a time, by extraction from P.

Some features of the described method are now illustrated through the following two examples.

EXAMPLE 1

FIGS. 3 to 5 provide computer code relating to a first example. In the first example, the program P has a main function main( ), and 5 functions func1( ), func2( ), func3( ), func4( ), func5( ). The line numbering in P is used to readily identify particular code segments. The digit to the left of the dot identifies the function: 0 for the main function, and 1 to 5, respectively, for the functions func1( ) to func5( ). The number to the right of the dot represents the sequential line number in a function.

The functions get_input( ), put_output( ), and sin( ) are assumed to be built-in functions. The canonical form chosen for conditional statements is the if-then-else construct. Further, in the C-like language on which the examples described herein are based, the function arguments are assumed to be passed by address and not by value.

The program P is recast into canonical form by converting the while construct in func3( ), and the switch-case construct in func4( ) in the computer code of FIGS. 6 to 8.

Once the set of tasks T={T₁, T₂, . . . T_(n)} is finalized, a hierarchical design of P_(R) can be formed in which the only functions M_(R) calls are the functions f_(0i), i=1, 2, . . . n. For illustration, consider the data sets for tasks T={T₁, T₂, T₃} as given below:

For T₁, the data set U₁={u₁₁} is

u₁₁={i, j, a, b}={10, 5, 2, 0}

For T₂, the data set U₂={u₂₁, u₂₂} is

u₂₁={i, j, b, c}={5, 10, 2, 0}

u₂₂={i, j, b, c}={5, 10, 2, 2}

For T₃, the data set U₃={u₃₁} is

u₃₁={i, j}={−1, 5}

Task T₁

For the test data u₁₁={i, j, a, b}={10, 5, 2, 0}, the extraction of code procedure provides c₁₁ as given in FIGS. 9 and 10.

Since there is only one test case:

C₁=c₁₁={f₀₁₁, f₁₁₁, f₃₁₁, f₄₁₁}=func0_(—)1, func1_(—)1, func3_(—)1, func4_(—)1}

Thus the merging of variants of a function is bypassed and the functions renamed as follows: “main” function f₀₁₁ to func0_(—)1, and of the remaining functions f₁₁₁ to func1_(—)1, f₃₁₁ to func3_(—)1, f₄₁₁, to func4_(—)1, so that C₁ is as given in FIGS. 11 and 12.

0Task T₂

For the test data u₂₁={i, j, b, c} {5, 10, 2, 0} and u₂₂={i, j, b, c}={5, 10, 2, 2}, the extracted codes c₂₁ and c₂₂ are found to be identical. One of these extracted codes, for example, c₂₂ can be deleted. In this respect, refer to the subsection entitled “Creation of components C₁, C₂, . . . C_(n) and M_(R), step 6”. On the other extracted code c₂₁, functions appearing therein are renamed and its “main” function converted to f₀₂₁=func0_(—)2 so that C₂=c₂₁={f₀₂₁, f₂₂₁, f₃₂₁, f₄₂₁}={func0_(—)2, func2_(—)2, func3_(—)2, func4_(—)2} is as given in FIGS. 13 and 14.

Task T₃

Since, there is only one test data u₃₁={i, j}={−1, 5} and the extracted code is rather small, one can easily see that C₃=c₃₁={f₀₃₁, f₅₃₁}={func0_(—)3, func5_(—)3} is as given in FIG. 15.

Now that C₁, C₂, and C₃ are available, merging of variants of different functions across C_(i), as described above in the subsection entitled “Merging variants of a function across C_(i)” is attempted.

Functions that fulfill the conditions of step 1 in the subsection entitled “Step 8—Merging variants of a function across C_(i)” are described as follows. Only one variant of func2( ) exists as func2_(—)2( ) in C₂ and the contents of func2_(—)2( ) are identical to those of func2( ). Thus the conditions of step 1 are fulfilled. Hence func2_(—)2( ) is removed from C₂ and a copy of func2( ) is placed in P_(R). Furthermore, all calls to func2_(—)2( ) in C₂ are changed to calls to func2( ). Similar action is taken on func5_(—)3( ).

Functions that fulfill the conditions of step 2 in the subsection entitled “Step 8—Merging variants of a function across C_(i)” are described as follows. Two variants of func3( ) exists as func3_(—)1( ) and func3_(—)2( ) in C₁ and C₂, respectively, and the contents of func3_(—)1( ) and func3_(—)2( ) are identical but different from the contents of func3( ). Thus the conditions of step 2 are fulfilled. Hence one of the variants, for example, func3_(—)2( ) is removed from C₂ and all calls to func3_(—)2( ) in C₂ are changed to calls to func3_(—)1( ). Similarly changes are performed on functions func4_(—)1( ) and func4_(—)2( ) (for example, delete func4_(—)2( ) and change all calls to func4_(—)2( ) in C₂ to calls to func4_(—)1( )). For func1( ), the alternative condition of step 2 applies. Hence, func1_(—)1( ) is retained.

Next, each version of main( ) is packaged as an ordinary function. This is usually straightforward in most programming languages and requires placing a return statement as the last executable statement in each version of main. In the C programming language, even placing a return statement may not be required, if the function's return type is explicitly stated as void. However, if a version of main has more than one exit point, appropriate return statements must be placed at each of those exit points.

The restructured program is given in FIGS. 16 to 19.

In this version, the following comment: “[Option: Put input checking code here.]” is placed after input statements to indicate that inserting code to check the inputs before proceeding further with the execution of P_(R) is generally advisable.

EXAMPLE 2

0In this example, some aspects of how multiple versions of a function may be merged into one are demonstrated. Consider the three versions of the function func( ) given in FIGS. 20 and 21.

When the bodies of the three functions are appended to one of them and sorted in ascending order of line numbers, the code given in FIGS. 22 and 23 is obtained.

Now, since lines 9.02, 9.04, 9.05, 9.06, 9.09, 9.21 to 9.25 each appear as multiple identical copies, all but one copy of each of these lines is deleted. Then, since line 9.03 has two copies of a declaration statement, the variables list (which now becomes a, b, c, x, y) is consolidated. Finally, lines 9.07, 9.08, and 9.10 to 9.19 are retained since only one copy each of them appear as given in FIG. 24.

Data Sets that Create Error Conditions in P

The input data sets are assumed not to lead to error conditions during execution. If this assumption is incorrect, the occurrence of error conditions can be used to advantage for debugging (for example) P, by handling the blank { }in the if-then-else constructs as noted earlier.

Note that during program execution, the statements being executed will be flagged. When an error occurs, all the flagged statements are collated, function definition by function definition. If a statement, which is not a call to a function, carries a flag of the first type, then that is the statement where the program aborted. However, the main advantage of using collated statements is that a comparison between the collated statements and program P can provide helpful clues as to what caused the error condition. This, of course, must be done manually.

Several possibilities exist for optimizing the method outlined in this disclosure. For example, functions that do not contain any conditional statements in them can be separately handled. These functions can be separately handled as these functions can be directly placed in P_(R) and, of these functions, those that are never called removed in the final editing of P_(R).

Another optimizing possibility is when in statements such as:

if ( . . . ) { . . . }

The portion { . . . } in the above statement does not contain any conditional or branching statement and no variables are modified inside ( . . . ), then this code can be replaced by { . . . } in the extracted version.

Likewise, additional special cases may be identified and handled separately. However, the handling of special cases will usually make the coding of the restructuring tool more complex.

Computer Hardware and Software

FIG. 25 is a schematic representation of a computer system 2500 that can be used to perform steps in a process that implements the techniques described herein. The computer system 2500 is provided for executing computer software, which is programmed to assist in performing the described techniques. This computer software executes under a suitable operating system installed on the computer system 2500.

The computer software involves a set of programmed logic instructions that are able to be interpreted by the computer system 2500 for instructing the computer system 2500 to perform predetermined functions specified by those instructions. The computer software can be an expression recorded in any language, code or notation, comprising a set of instructions intended to cause a compatible information processing system to perform particular functions, either directly or after conversion to another language, code or notation.

The computer software is programmed by a computer program comprising statements in an appropriate computer language. The computer program is processed using a compiler into computer software that has a binary format suitable for execution by the operating system. The computer software is programmed in a manner that involves various software components, or code means, that perform particular steps in the process of the described techniques.

The components of the computer system 2500 include: a computer 2520, input devices 2510, 2515 and video display 2590. The computer 2520 includes: processor 2540, memory module 2550, input/output (I/O) interfaces 2560, 2565, video interface 2545, and storage device 2555.

The processor 2540 is a central processing unit (CPU) that executes the operating system and the computer software executing under the operating system. The memory module 2550 includes random access memory (RAM) and read-only memory (ROM), and is used under direction of the processor 2540.

The video interface 2545 is connected to video display 2590 and provides video signals for display on the video display 2590. User input to operate the computer 2520 is provided from input devices 2510, 2515 consisting of keyboard 2510 and mouse 2515. The storage device 2555 can include a disk drive or any other suitable non-volatile storage medium.

Each of the components of the computer 2520 is connected to a bus 2530 that includes data, address, and control buses, to allow these components to communicate with each other via the bus 2530.

The computer system 2500 can be connected to one or more other similar computers via a input/output (I/O) interface 2565 using a communication channel 2585 to a network 2580, represented as the Internet.

The computer software program may be provided as a computer program product, and recorded on a portable storage medium. In this case, the computer software program is accessed by the computer system 2500 from the storage device 2555. Alternatively, the computer software can be accessed directly from the network 2580 by the computer 2520. In either case, a user can interact with the computer system 2500 using the keyboard 2510 and mouse 2515 to operate the programmed computer software executing on the computer 2520.

The computer system 2500 is described for illustrative purposes: other configurations or types of computer systems can be equally well used to implement the described techniques. The foregoing is only an example of a particular type of computer system suitable for implementing the described techniques.

CONCLUSION

A method, a computer system, and computer software for restructuring computer programs are described herein. Those experienced in the techniques of compiler writing can implement the restructuring method since similar programming skills are required in both. While the described techniques are particularly of benefit in restructuring legacy computer codes for improved maintainability, the described techniques are also of use in restructuring modern codes to improve their robustness and for fixing programming errors.

Various alterations and modifications can be made to the techniques and arrangements described herein, as would be apparent to one skilled in the relevant art. 

1. A method of restructuring a source computer program to a target computer program, the method comprising: defining a source computer program P that consists of source code, said source code of the source computer program P comprising a main function F₀ and a set of functions {F₁, F₂, . . . F_(r)}, wherein F₁, F₂, . . . F_(r) are each a function other than the main function F₀ and are each adapted return a value to the main function F₀ as a result of being executed in response to being called by the main function F₀, wherein each function in the set of functions {F₁, F₂, . . . F_(r)} is external to the main program F₀ and comprises one or more statements and/or declarations, and wherein r is at least 1; defining for said source computer program P, a set of tasks T={T₁, T₂, . . . T_(n)} able to be performed by said source computer program P, wherein n is at least 1; determining, for each task T_(i) in said set of tasks T, a corresponding set of input data sets U_(i)={u_(i1), u_(i2), . . . u_(ip)} for task T_(i), wherein p is a function of i denoted asp(i) such that p(i) is at least 1, and wherein each input data set u_(ij) in U_(i) consists of an explicit data value of at least one variable in P; and determining, for each set of input data sets U_(i)={u_(i1), u_(i2), . . . u_(ip)} a corresponding set of programs {c_(i1), c_(i2), . . . c_(ip)}such that each program c_(ij) in the set of programs {c_(i1), c_(i2), . . . c_(ip)} comprises declarations and executable statements from the source code of P required to execute task T_(i) for input data set u_(ij) in U_(i); processing each set of programs {c_(i1), c_(i2), . . . c_(ip)} to generate a component C_(i) adapted to execute the respective task T_(i), said processing resulting in generation of a set of components C={C₁, C₂, . . . C_(n)}; and generating a target computer program P_(R) from the set of components C, such that P_(R) comprises a main program H₀ and a set of functions H={H₁, H₂, . . . H_(n)}.
 2. The method of claim 1, wherein the set of functions H is derived from the set of components C such that H_(i) is derived from C_(i) for i=1, 2, . . . n.
 3. The method of claim 1, wherein the main program H₀ comprises at least one conditional statement adapted to call each function H_(i) in the set of functions H to execute the task T_(i) upon the at least one conditional statement encountering the task T_(i).
 4. The method of claim 1, wherein the method further comprises converting all statements of said functions {F₀, F₁, F₂, . . . F_(r)} of said source computer program P having a same logical functionality but a different form to a same predetermined canonical form, and wherein said source computer program P comprises a first and second group of statements having a same logical functionality but a different form.
 5. The method of claim 1, wherein said set of input data sets U_(i)={u_(i1), u_(i2), . . . u_(ip)} collectively provide complete coverage of all possible activities within task T_(i) for fully executing respective task T_(i).
 6. The method of claim 1, wherein data boundaries for task T_(i) are known to a user, and said data boundaries are accounted for in respective set of input data sets U_(i) such that activities pertinent to respective task T_(i) alone and no other are executed.
 7. The method of claim 1, wherein none of the input data sets {u_(i1), u_(i2), . . . u_(ip)} of the set of input data sets U_(i) creates error conditions when used as input to the respective task T_(i) of said source computer program P.
 8. The method of claim 1, wherein said target computer program P_(R) comprises a function M_(R) that is a restructured main function for said target computer program P_(R) whose principal task is to ascertain which task the user wishes to invoke and ensure the execution of the corresponding component C_(i) to execute the task.
 9. The method of claim 1, wherein each of said components C_(i) comprises a respective set of functions {F_(0i), F_(1i), F_(2i), . . . F_(ri)} in which (i) F_(0i) contains all declarations and executable statements extracted from function F₀ in the context of executing respective task T_(i) and (ii) each F_(ki) for k 0 contains all declarations and executable statements extracted from respective function F_(k).
 10. The method of claim 1, wherein the structure of said target computer program P_(R) is such that if a task T_(j) of said source computer program P is changed or removed, the corresponding respective component C_(j) and function F_(0j) of the target computer program is changed or removed.
 11. The method of claim 1, wherein the method further comprises manually optimizing the target computer program P_(R).
 12. The method of claim 11, wherein said manually optimizing comprises making each task of the set of tasks T run faster via the target computer program P_(R) than via the source computer program P.
 13. The method of claim 1, wherein p(1) is at least
 2. 14. The method of claim 13, wherein c₁₂=c₁₁, and wherein said processing comprises eliminating c₁₁ such that the component C₁ includes statements and/or declarations from c₁₂ and not from c₁₁.
 15. The method of claim 13, wherein c₁₁ comprises a function f₁, wherein c₁₂ comprises a function f₂, wherein f₁=f₂, and wherein said processing comprises eliminating f₁ such that the component C₁ includes f₂ and does not include f₁.
 16. The method of claim 13, wherein c₁₁ comprises a function f₁, wherein c₁₂ comprises a function f₂, wherein f₁ and f₂ have common declarations and different bodies, and wherein said processing comprises merging f₁ and f₂ to generate a function f₃ that comprises the bodies of f₁ and f₂ merged together and the declarations of f₁ and f₂ merged together such that the common declarations of only f₁ and not of f₂ appear in the merged declarations of f₃.
 17. The method of claim 1, wherein n is at least 2, and wherein p(2) is unequal to p(1).
 18. The method of claim 1, wherein n is at least 2, and wherein said generating the target computer program P_(R) comprises merging N functions within the set of components C into M functions within the set of functions H such that M is less than N.
 19. The method of claim 1, wherein the least one conditional statement comprises an if-then-else statement.
 20. The method of claim 1, wherein the least one conditional statement encounters the task T_(i). upon the determining that a task identification variable (task_id) matches an identifier of the task T_(i).
 21. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said memory unit containing instructions that when executed by the processor implement the method of claim
 1. 22. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, said computer readable program code containing instructions that when executed by a processor of a computer system implement the method of claim
 1. 23. A method of restructuring a source computer program to a target computer program, the method comprising the steps of: defining a source computer program P that consists of source code, said source code of the source computer program P comprising a set of functions {F₀, F₁, F₂, . . . F_(r)}, each function of which comprises one or more statements and/or declarations; defining for said source computer program P, a set of tasks T={T₁, T₂, . . . T_(n)} able to be performed by said source computer program P; determining, for each of the tasks T_(i) in said set of tasks T, a corresponding set of input data sets U_(i)={u_(i1), u_(i2), . . . u_(ip)} for task T_(i); restructuring said source computer program P into a target computer program P_(R) that consists of source code.
 24. The method of claim 23, wherein said source code of the target computer program P_(R) comprises a set of components {C₁, C₂, . . . C_(n)} with reference to the interaction of said input data sets U_(i) with said set of tasks T, and wherein each component C_(i) of said set of components of said target computer program P_(R) consists of source code that contains declarations and executable statements that are extracted from the source code of said source computer program P and required to execute the respective task T_(i) of said source computer program P corresponding with the component C_(i);
 25. The method of claim 23, wherein the method further comprises interpreting said source computer program P with each of said input data sets U_(i) related to respective tasks T_(i).
 26. The method of claim 23, wherein the method further comprises flagging each interpreted statement of said source computer program P with one or more predetermined flags.
 27. The method of claim 27, wherein said predetermined flags include: (i) a first flag that indicates that the flagged statement has started execution; (ii) a second flag that indicates that the flagged statement has finished execution; and (iii) a third flag that indicates that the flagged statement has executed one or more times previously during execution of the source computer program P with the same input data u_(ij).
 28. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said memory unit containing instructions that when executed by the processor implement the method of claim
 23. 29. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, said computer readable program code containing instructions that when executed by a processor of a computer system implement the method of claim
 23. 